Non linear image analysis for fuzzy classification of breast cancer

E. Martinez Marroquin, C. Vos, E. Santamaria, X. Jove, J. C. Socoro

Research output: Contribution to conference (non-published works)Paperpeer-review

5 Citations (Scopus)

Abstract

Non linear image processing proves to be a powerful tool for segmenting images preserving only the interesting regions; those are the cells' nucleous (CN) in this application. All CN are preserved and identified even if they are in a cluster, while the rest of the image is considered to be part of the background. The morphological segmentation makes it possible to calculate outstanding features that could not be obtained by simple observation. These are passed to a fuzzy classifier which decides the probability of the biopsy to belong to a high or low cancer level. Obtaining these measures by human observation is a hard, and nonprecise task. The extracted features will make it possible to reach a parametric classification that is more efficient than the subjective classification made by human observation.

Original languageEnglish
Pages943-946
Number of pages4
Publication statusPublished - 1996
Externally publishedYes
EventProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) - Lausanne, Switz
Duration: 16 Sep 199619 Sep 1996

Conference

ConferenceProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3)
CityLausanne, Switz
Period16/09/9619/09/96

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